Research Engineer: AI & Optimization for Vehicle Routing

Singapore Management University; Singapore; Hybrid; SGD 60,000 - 90,000; Full time

Job summary

Singapore Management University is seeking a research-focused candidate to design and develop world models for vehicle routing problems. You will integrate these models with neural solvers and planning methods to drive decision making in complex optimization tasks.

Responsibilities include implementing baselines, evaluating on datasets, and preparing technical documentation and publications. Strong AI foundations and communication skills are essential for collaboration in a small academic team.

Qualifications

• Master degree in Computer Science, Information Technology or Information Systems with AI focus.
• At least one year of research or development experience in reinforcement learning or related areas.
• Knowledge of world models, generative modelling and optimization techniques.
• Ability to design rigorous experiments, benchmarks and reproduce results.
• Strong foundations in algorithms, data structures and mathematical reasoning.
• Publications or substantial project work in AI/optimization are advantageous.
• Clear written and verbal communication; able to work independently in a small research team.

Responsibilities

• Design and develop world models that learn compact representations of VRP states.
• Integrate models with neural solvers, planning, search or RL methods for decision making.
• Implement neural and traditional baselines and evaluate on VRP datasets.
• Prepare research papers, technical documentation and reusable code.
• Undertake other duties as assigned.

Skills

Reinforcement learning

Experiment design

Communication skills

Independent yet collaborative

Graph neural networks

Education

Master's degree in CS/IT/IS

Job description

Singapore Management University is seeking a research-focused candidate to design and develop world models for vehicle routing problems. You will integrate these models with neural solvers and planning methods to drive decision making in complex optimization tasks.

Responsibilities include implementing baselines, evaluating on datasets, and preparing technical documentation and publications. Strong AI foundations and communication skills are essential for collaboration in a small academic team.